期刊文献+
任意字段
题名或关键词
题名
关键词
文摘
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息

微分进化微粒群算法及其控制 被引量：4

Differential evolutionary particle swarm optimization with controller
下载PDF
导出
摘要 通过对微粒群优化算法的分析,提出了一种用微分方程组描述的微粒群优化算法——微分进化微粒群优化(DEPSO)算法,并利用传递函数对DEPSO算法的收敛性进行分析.在此基础上,通过引入PID控制器以控制DEPSO算法的动态进化行为,以增强微粒产生的多样性,从而改进微粒群优化算法的全局收敛性.仿真结果表明了此方法的有效性. Through analysis to particle swarm optimization （PSO） algorithm, a new modified particle swarm optimization algorithm described by differential equation-differential evolutionary particle swarm optimization （DEPSO） algorithm is proposed, and the convergence of this algorithm is analyzed with translation function. To enhance the diversity of swarm and improve the global convergence of PSO algorithm, PID controller is introduced to control dynamic evolutionary behavior of DEPSO algorithm. Simulation results are proved to illustrate the effectiveness of the algorithm.
作者 曾建潮 崔志华
机构地区 太原科技大学系统仿真与计算机应用研究所
出处 《系统工程学报》 CSCD 北大核心 2007年第3期328-332,共5页 Journal of Systems Engineering
基金 国家自然科学基金资助项目(60674104)
关键词 微粒群算法 微分进化微粒群算法 PID控制器 particle swarm optimization differential evolutionary particle swarm optimization PID controller
分类号 TP18 [自动化与计算机技术—控制理论与控制工程]
  • 相关文献

参考文献11

  • 1Kennedy J,Eberhart R.Particle swarm optimization[A].In:IEEE International Conference on Neural Networks[C].Perth,Australia:1995,1942-1948.
  • 2Eberhart R,Kennedy J.A new optimizer using particle swarm theory[A].In:The Sixth International Symposium on Micro Machine and Human Science[C].Nagoya,Japan:1995.39-43.
  • 3Wachowiak M P,Smolikova R,Zheng Y F,et al.An approach to multimodal biomedical image registration utilizing particle swarm optimization[J].IEEE Trans.on Evolutionary Computation,2004,8(3):289-301.
  • 4Srinivasan D,Loo W H,Cheu R L.Traffic incident detection using particle swarm optimization[A].In:Proceedings of 2003 IEEE Swarm Intelligence Symposium[C].Indianapolis,U.S.A.:2003.144-151.
  • 5Shi Y,Eberhart R C.A modified particle swarm optimizer[A].In:Proceedings of IEEE Internation,Conference of Evolutionary Computation[C].Anchorage,U.S.A.:1998.197-204.
  • 6Clerc M.The swarm and the queen:Toward a deterministic and adaptive particle swarm optimization[A].In:Proceedings of the Congress on Evolutionary Computation[C].Washington D.C.,U.S.A.:1999.1951-1957.
  • 7van den Bergh F,Engelbrecht A P.A cooperative approach to particle swarm optimization[J].IEEE Trans.on Evolutionary Computation,2004,8(3):225-239.
  • 8谭瑛,曾建潮,高慧敏.基于离散时间线性系统理论的微粒群算法分析[A].In:Proceedings of 5th World Congress on Intelligent Control and Automation[C].Hangzhou,China:2004.2210-2213.
  • 9Clerc M,Kennedy J.The particle swarm-explosion,stability,and convergence in a multidimensional complex space[J].IEEE Trans.on Evolutionary Computation,2002,6(1):58-73.
  • 10Bergh F.An Analysis of Particle Swarm Optimizers[D].Pretoria:University of Pretoria,2001.

二级参考文献7

  • 1P N Suganthan. Particle swarm optimiser with neighbourhood operator. In: Proc of the Congress on Evolutionary Computation.Piscataway, NJ: IEEE Service Center, 1999. 1958～1962
  • 2E Ozcan, C Mohan. Particle swarm optimization: Surfing the waves. In: Proc of the Congress on Evolutionary Computation.Piscataway, NJ: IEEE Service Center, 1999. 1939～1944
  • 3M Clerc, J Kennedy. The particle swarm: Explosion, stability and convergence in a multi-dimensional complex space. IEEE Trans on Evolutionary Computation, 2002, 6(1): 58～73
  • 4F Solis, R Wets. Minimization by random search techniques.Mathematics of Operations Research, 1981, 6(1 ): 19～ 30
  • 5F Van den Bergh. An analysis of particle swarm optimizers: [ Ph D dissertation]. Pretoria: University of Pretoria, 2001
  • 6王凌.智能优化算法及其应用.北京:清华大学出版社,2001( Wang Ling. Intelligent Optimization Algorithms with Applications( in Chinese) . Beijing: Tsinghua University Press,2001)
  • 7J Holland. Adaption in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press, 1975

共引文献159

同被引文献36

引证文献4

二级引证文献6

系统工程学报
2007年 第3期

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部